Unlocking Productivity : Revealing Waste and Hidden Disturbances Impacting MEP Workers

Christopher Görsch*, Olli Seppänen, Antti Peltokorpi, Rita Lavikka

*Tämän työn vastaava kirjoittaja

Tutkimustuotos: LehtiartikkeliArticleScientificvertaisarvioitu

33 Lataukset (Pure)

Abstrakti

Wasted effort limits productivity. Successful construction project management entails identifying and mitigating causes of waste. A time-motion study was conducted to collect and classify mechanical, electrical, and plumbing (MEP) work to understand factors contributing to waste. The data were analyzed for disturbances to direct work and sources of waste within such disturbances. Installation work was disturbed very frequently. This led to low shares of direct work. Disturbances can be divided into three groups (short-, medium-, and long-term) based on duration. Short-term disturbances, involving adjusting installation areas and material handling, enabled continued direct work without waste. Medium-term disturbances included most nonvalue-adding activities within the wider work environment. They depended on installers' understanding and required workplace adjustments. Long-term disturbances extended beyond the installation area, necessitating material searches and coordination, leading to significant waste. The study contributes to understanding MEP work and questions traditional management practices that do not provide sufficient preconditions for construction workers. Current methods are not on a sufficient level of granularity to effectively improve productivity. The study suggests integrating precise motion tracking and digital systems to reduce waste related to medium- and long-term disturbances. Providing real-time, task-specific information using digital tools can enhance situational awareness, minimizing nonvalue-adding tasks. Additionally, mobile workstations and logistical services could alleviate movement issues in such disturbances. Required granularity to accurately assess preconditions requires additional research into automating data collection and analysis.

AlkuperäiskieliEnglanti
Artikkeli04024108
Sivumäärä20
JulkaisuJournal of Construction Engineering and Management: ASCE
Vuosikerta150
Numero9
DOI - pysyväislinkit
TilaJulkaistu - 1 syysk. 2024
OKM-julkaisutyyppiA1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä

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